Experience with analysis and creation of data pipelines, data architecture, ETL/ELT development and

with processing structured and unstructured data

Proven experience with using data stored in RDBMSs and experience or good understanding of NoSQL databases

Ability to write performant Scala code and SQL statements

Ability to design with a focus on solutions that are fit for purpose whilst keeping options open for future

needs

Ability to analyze data, identify issues (e.g. gaps, inconsistencies) and troubleshoot these

Have a truly agile mindset, capable and willing to take on tasks outside of her/his core competencies to

help the team

Experience in working with customers to identify and clarify requirements

Strong verbal and written communication skills, good customer relationship skills  

Strong interest in the financial industry and related data.

 

 

Will be considered as assets: 

 

Knowledge of Python and Spark

Understanding of the Hadoop ecosystem including Hadoop file formats like Parquet and ORC

Experience with open source technologies used in Data Analytics like Spark, Pig, Hive, HBase, Kafka, …

Ability to write MapReduce & Spark jobs

Knowledge of Cloudera

Knowledge of IBM mainframe

Knowledge of AGILE development methods such as SCRUM is clearly an asset.